examples/python/lerobot/README.md
https://vimeo.com/983024799?autoplay=1&loop=1&autopause=0&background=1&muted=1&ratio=1920:1080
LeRobot is a project by huggingface that aims to provide models, datasets and tools for real-world robotics in PyTorch. This example shows how one can train a model on the pusht-dataset and visualize it's progress using rerun.
This is an external example, check the repository for more information.
To train the model as shown in the video, install git-lfs and clone the repository and then run the following code:
pip install -e '.[pusht]'
WANDB_MODE=offline python lerobot/scripts/train.py \
hydra.run.dir=outputs/train/diffusion_pusht \
hydra.job.name=diffusion_pusht \
policy=diffusion \
env=pusht \
env.task=PushT-v0 \
dataset_repo_id=lerobot/pusht \
training.offline_steps=20000 \
training.save_freq=5000 ++training.log_freq=50 \
training.eval_freq=1500 \
eval.n_episodes=50 \
wandb.enable=true \
wandb.disable_artifact=true \
device=cuda
If you don't have CUDA installed you will have to change the last argument device=cuda to device=cpu or another device.